•Design and develop ADAS ground truth system perception algorithm, incl. multi-sensor fusion detection and segmentation algorithm, tracking algorithm, process cloud pipeline, etc.

•Design and develop innovative multi-model fusion algorithms such as map fusion modules, multi-frame local map construction modules, and road network construction modules based on static environment and dynamic objects perception results and offline maps, etc.

•Performance optimization for sensor fusion models in vehicle application.

•Cooperate with Bosch business units in China and worldwide for requirement analysis, technology transfer, and evaluate market attractiveness of new technical solutions.

Qualifications Requirement

•Master’s degree or above with major in Automotive/Automation/Computer Science/Artificial Intelligence/Electrical Engineering/Mechatronics or related.

•More than 3 years working experience in automotive electronics, experienced in ADAS, perception fusion.

•Strong knowledge in the perception domain, such as object detection, object tracking, semantic segmentation, and depth estimation based on camera/LiDAR.

•Professional English: able to use English fluently and accurately (speaking, listening, reading and writing).

Job Relevant Knowledge and Experience

•Familiarity with open-source vision libraries such as OpenCV and PCL

•Familiarity with AI-based perception backbone, frameworks, and model training

•Familiarity with filtering and optimization algorithms

•Experience in local map construction, lane detection, perception & map fusion, perception result fusion, and PnC is a strong plus

•Experience in ADAS sensors, such as cameras, LiDARs, and radars; familiarity with SD/HD map data structure is a strong plus

•Proficiency and practical experiences in ROS, Python, or C++, and developing in Linux